Synchronized Progression of Prestin Expression and Auditory Brainstem Response during Postnatal Development in Rats

Prestin is the motor protein expressed in the cochlear outer hair cells (OHCs) of mammalian inner ear. The electromotility of OHCs driven by prestin is responsible for the cochlear amplification which is required for normal hearing in adult animals. Postnatal expression of prestin and activity of OHCs may contribute to the maturation of hearing in rodents. However, the temporal and spatial expression of prestin in cochlea during the development is not well characterized. In the present study, we examined the expression and function of prestin from the OHCs in apical, middle, and basal turns of the cochleae of postnatal rats. Prestin first appeared at postnatal day 6 (P6) for basal turn, P7 in middle turn, and P9 for apical turn of cochlea. The expression level increased progressively over the next few days and by P14 reached the mature level for all three segments. By comparison with the time course of the development of auditory brainstem response for different frequencies, our data reveal that prestin expression synchronized with the hearing development. The present study suggests that the onset time of hearing may require the expression of prestin and is determined by the mature function of OHCs

Preparation of total triterpenoids from Antrodia cinnamomea fermentation mycelium and their in vitro inhibitory effects on hepatocellular carcinoma

Abstract Total triterpenoids from Antrodia cinnamomea fermentation mycelium (TT-ACFM) were prepared, and their in vitro inhibitory effects on hepatocellular carcinoma were investigated. Human hepatocellular carcinoma HepG2 cells were incubated with TT-ACFM with concentration of 0 (control), 12.5, 25, 50, 100 and 200 μg/mL, respectively. The proliferation of cell was detected using CCK-8 method. The apoptosis of cells was detected by flow cytometry. The migration and invasion of cells was determined using Transwell chamber. The level of reactive oxygen species (ROS) in cells was determined using DCFH-DA method. The expressions of matrix metalloproteinse-2 (MMP-2), matrix metalloproteinse-9 (MMP-9) and vascular endothelial growth factor (VEGF) protein in cells were detected by western blot assays. Results indicate that, TT-ACFM can not only inhibit the proliferation of HepG2 cells and promote their apoptosis, but also inhibit their invasion and invasion. The mechanism may be related to its increase of ROS and down-regulation of MMP-2, MMP-9 and VEGF expression in cells

Pre-training on Synthetic Driving Data for Trajectory Prediction

Accumulating substantial volumes of real-world driving data proves pivotal in the realm of trajectory forecasting for autonomous driving. Given the heavy reliance of current trajectory forecasting models on data-driven methodologies, we aim to tackle the challenge of learning general trajectory forecasting representations under limited data availability. We propose to augment both HD maps and trajectories and apply pre-training strategies on top of them. Specifically, we take advantage of graph representations of HD-map and apply vector transformations to reshape the maps, to easily enrich the limited number of scenes. Additionally, we employ a rule-based model to generate trajectories based on augmented scenes; thus enlarging the trajectories beyond the collected real ones. To foster the learning of general representations within this augmented dataset, we comprehensively explore the different pre-training strategies, including extending the concept of a Masked AutoEncoder (MAE) for trajectory forecasting. Extensive experiments demonstrate the effectiveness of our data expansion and pre-training strategies, which outperform the baseline prediction model by large margins, e.g. 5.04%, 3.84% and 8.30% in terms of $MR_6$, $minADE_6$ and $minFDE_6$

RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN

The second-order training methods can converge much faster than first-order optimizers in DNN training. This is because the second-order training utilizes the inversion of the second-order information (SOI) matrix to find a more accurate descent direction and step size. However, the huge SOI matrices bring significant computational and memory overheads in the traditional architectures like GPU and CPU. On the other side, the ReRAM-based process-in-memory (PIM) technology is suitable for the second-order training because of the following three reasons: First, PIM's computation happens in memory, which reduces data movement overheads; Second, ReRAM crossbars can compute SOI's inversion in $O\left(1\right)$ time; Third, if architected properly, ReRAM crossbars can perform matrix inversion and vector-matrix multiplications which are important to the second-order training algorithms. Nevertheless, current ReRAM-based PIM techniques still face a key challenge for accelerating the second-order training. The existing ReRAM-based matrix inversion circuitry can only support 8-bit accuracy matrix inversion and the computational precision is not sufficient for the second-order training that needs at least 16-bit accurate matrix inversion. In this work, we propose a method to achieve high-precision matrix inversion based on a proven 8-bit matrix inversion (INV) circuitry and vector-matrix multiplication (VMM) circuitry. We design \archname{}, a ReRAM-based PIM accelerator architecture for the second-order training. Moreover, we propose a software mapping scheme for \archname{} to further optimize the performance by fusing VMM and INV crossbar. Experiment shows that \archname{} can achieve an average of 115.8$\times$/11.4$\times$ speedup and 41.9$\times$/12.8$\times$energy saving compared to a GPU counterpart and PipeLayer on large-scale DNNs.Comment: 13pages, 13 figure

HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation

Heterogeneous graph neural networks (HGNNs) have emerged as powerful algorithms for processing heterogeneous graphs (HetGs), widely used in many critical fields. To capture both structural and semantic information in HetGs, HGNNs first aggregate the neighboring feature vectors for each vertex in each semantic graph and then fuse the aggregated results across all semantic graphs for each vertex. Unfortunately, existing graph neural network accelerators are ill-suited to accelerate HGNNs. This is because they fail to efficiently tackle the specific execution patterns and exploit the high-degree parallelism as well as data reusability inside and across the processing of semantic graphs in HGNNs. In this work, we first quantitatively characterize a set of representative HGNN models on GPU to disclose the execution bound of each stage, inter-semantic-graph parallelism, and inter-semantic-graph data reusability in HGNNs. Guided by our findings, we propose a high-performance HGNN accelerator, HiHGNN, to alleviate the execution bound and exploit the newfound parallelism and data reusability in HGNNs. Specifically, we first propose a bound-aware stage-fusion methodology that tailors to HGNN acceleration, to fuse and pipeline the execution stages being aware of their execution bounds. Second, we design an independency-aware parallel execution design to exploit the inter-semantic-graph parallelism. Finally, we present a similarity-aware execution scheduling to exploit the inter-semantic-graph data reusability. Compared to the state-of-the-art software framework running on NVIDIA GPU T4 and GPU A100, HiHGNN respectively achieves an average 41.5$\times$ and 8.6$\times$ speedup as well as 106$\times$ and 73$\times$ energy efficiency with quarter the memory bandwidth of GPU A100

Causal relationship between gut microbiota and differentiated thyroid cancer: a two-sample Mendelian randomization study

BackgroundThe gut microbiota has been significantly associated with differentiated thyroid cancer (DTC). However, the causal relationship between the gut microbiota and DTC remains unexplored.MethodsGenome-wide association study (GWAS) summary databases were utilized to select exposures and outcomes. The Mendelian randomization (MR) method was employed to investigate the causal relationship between the gut microbiota and DTC. A sensitivity analysis was performed to assess the reliability of the findings.ResultsFour bacterial traits were associated with the risk of DTC: Class Mollicutes [odds ratio (OR) = 10.953, 95% confidence interval (95% CI): 2.333–51.428, p = 0.002], Phylum Tenericutes (OR = 10.953, 95% CI: 2.333–51.428, p = 0.002), Genus Eggerthella (OR = 3.219, 95% CI: 1.033–10.024, p = 0.044), and Order Rhodospirillales (OR = 2.829, 95% CI: 1.096–7.299, p = 0.032). The large 95% CI range for the Class Mollicutes and the Phylum Tenericutes may be attributed to the small sample size. Additionally, four other bacterial traits were negatively associated with DTC: Genus Eubacterium fissicatena group (OR = 0.381, 95% CI: 0.148–0.979, p = 0.045), Genus Lachnospiraceae UCG008 (OR = 0.317, 95% CI: 0.125–0.801, p = 0.015), Genus Christensenellaceae R-7 group (OR = 0.134, 95% CI: 0.020–0.886, p = 0.037), and Genus Escherichia Shigella (OR = 0.170, 95% CI: 0.037–0.769, p = 0.021).ConclusionThese findings contribute to our understanding of the pathological mechanisms underlying DTC and provide novel insights for the clinical treatment of DTC

Occurrences and distribution characteristics of organophosphate ester flame retardants and plasticizers in the sediments of the Bohai and Yellow Seas, China

Concentrations and distribution characteristics of organophosphate esters (OPEs) in surface sediment samples were analyzed and discussed for the first time in the open Bohai Sea (BS) and YellowSea (YS). Three halogenated OPEs [ tris-(2-chloroethyl) phosphate (TCEP), tris-(1-chloro-2-propyl) phosphate (TCPP), and tris-(1,3-dichloro2- propyl) phosphate (TDCPP)] and five non-halogenated OPEs [ tri-isobutyl phosphate (TiBP), tri-n-butyl phosphate (TnBP), tripentyl phosphate (TPeP), triphenyl phosphate (TPhP) and tris-(2-ethylhexyl) phosphate (TEHP)] were detected in this region. The concentrations of eight OPEs in total (Sigma 8OPEs) ranged from 83 to 4552 pg g(-1) dry weight (dw). The halogenated OPEs showed higher abundances than the non-halogenated ones did, with TCEP, TCPP, and TEHP the main compounds. Generally, concentrations of OPEs in the BS were higher than those in the YS. Riverine input (mainly the Changjiang DilutedWater (CDW)) and deposition effect in the mud areas might have influenced the spatial distributions of OPEs. Correlation between OPE concentrations and total organic carbon (TOC) indicated TOC was an effective indicator for the distribution of OPEs. Inventory analysis of OPEs implied that sea sediment might not be the major reservoir of these compounds. (C) 2017 Elsevier B.V. All rights reserved.</p

Distinct lesion features and underlying mechanisms in patients with acute multiple infarcts in multiple cerebral territories

ObjectiveTo determine the etiology spectrum and lesion distribution patterns of patients with acute multiple infarcts in multiple cerebral territories (AMIMCT) and provide guidance for treatment and prevention strategies in these patients.MethodsPatients with acute ischemic stroke diagnosed using diffusion-weighted imaging (DWI) were consecutively included in this study between June 2012 and Apr 2022. AMIMCT was defined as non-contiguous focal lesions located in more than one cerebral territory with acute neurological deficits. We retrospectively analyzed the clinical and imaging characteristics, etiology spectra and underlying mechanisms in patients with and without AMIMCT. Infarct lesion patterns on DWI and their relevance to etiology were further discussed.ResultsA total of 1,213 patients were enrolled, of whom 145 (12%) were diagnosed with AMIMCT. Patients with AMIMCT tended to be younger (P = 0.016), more often female (P = 0.001), and exhibited less common conventional vascular risk factors (P &lt; 0.05) compared to those without AMIMCT. The constitution of the Trial of Org 10,172 in Acute Stroke Treatment classification was significantly different between patients with and without AMIMCT (P = 0.000), with a higher proportion of stroke of other determined causes (67.6% vs. 12.4%). For detailed etiologies, autoimmune or hematologic diseases were the most common (26.2%) etiologies of AMIMCT, followed by periprocedural infarcts (15.2%), cardioembolism (12.4%), tumor (12.4%), large artery atherosclerosis (10.3%), and sudden drop in blood pressure (8.3%). Hypercoagulability and systemic hypoperfusion are common underlying mechanisms of AMIMCT. Distinctive lesion distribution patterns were found associated with stroke etiologies and mechanisms in AMIMCT. Most of patients with large artery atherosclerosis (73.3%), autoimmune/hematologic diseases (57.9%) manifested the disease as multiple infarct lesions located in bilateral supratentorial regions. However, 66.7% of cardioembolism and 83.8% of cardiovascular surgery related stroke presented with both supratentorial and infratentorial infarct lesions.ConclusionThe etiologies and mechanisms of patients with AMIMCT were more complex than those without AMIMCT. The distribution characteristics of infarct lesions might have important implications for the identification of etiology and mechanism in the future, which could further guide and optimize clinical diagnostic strategies